Elimination of useless neurons in incremental learnable self-organizing map

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

We propose a method to eliminate unnecessary neurons in Variable-Density Self-Organizing Map. We have defined an energy function which denotes the error of the map, and optimize the energy function by using graph cut algorithm. We conducted experiments to investigate the effectiveness of our approach.

Original languageEnglish
Title of host publicationAdvances in Self-Organizing Maps - 7th International Workshop, WSOM 2009, Proceedings
Pages264-271
Number of pages8
DOIs
Publication statusPublished - Aug 27 2009
Event7th International Workshop on Self-Organizing Maps, WSOM 2009 - St. Augustine, FL, United States
Duration: Jun 8 2009Jun 10 2009

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume5629 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other7th International Workshop on Self-Organizing Maps, WSOM 2009
CountryUnited States
CitySt. Augustine, FL
Period6/8/096/10/09

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

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  • Cite this

    Shimada, A., & Taniguchi, R. I. (2009). Elimination of useless neurons in incremental learnable self-organizing map. In Advances in Self-Organizing Maps - 7th International Workshop, WSOM 2009, Proceedings (pp. 264-271). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5629 LNCS). https://doi.org/10.1007/978-3-642-02397-2_30